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Record W4206408059 · doi:10.22481/reed.v2i6.10117

FORMAÇÃO DOCENTE: O INSTITUÍDO NO TERRITÓRIO DE IDENTIDADE DO SUDOESTE BAIANO

2021· article· pt· W4206408059 on OpenAlexfundno aff
Daniela Oliveira Vidal da Silva, Cláudio Pinto Nunes

Bibliographic record

VenueRevista de Estudos em Educação e Diversidade - REED · 2021
Typearticle
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsnot available
FundersUniversidade Federal do Rio Grande do NorteUniversidade Estadual do Sudoeste da BahiaUniversidade Federal de Minas GeraisConselho Nacional de Desenvolvimento Científico e TecnológicoUniversidade de CoimbraUniversité du Québec à Chicoutimi
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

O presente estudo busca analisar a categoria formação enquanto um dos critérios para a valorização docente e que é subdividida em inicial e continuada. A análise será realizada a partir do instituído nas legislações brasileiras e nos Planos de Cargo, Carreira e Remuneração (PCCR’s) que são utilizados para garantir direitos e criar estratégias para a valorização docente. O campo de pesquisa delimitado é o Território de Identidade do Sudoeste Baiano (TISOBA) e o estudo segue o viés metodológico da pesquisa documental. Os resultados encontrados nos permitem inferir que, embora o Plano de Cargo, Carreira e Remuneração seja pensado para ser um elemento legal de luta e resistência em favor da valorização docente, em alguns municípios esse documento ainda não se configura, de fato, como tal, visto que este dispositivo ainda não foi implementado e/ou atualizado, o que impacta e causa inconsistências no cumprimento de metas estabelecidas por legislações brasileiras que normatizam a formação inicial e continuada dos docentes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0060.003
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.361
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

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